Threshold Tracking System for Real-Time Event Analysis
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Solution Overview
Problem
Real-time analysis of multiple events from disparate sources faces challenges due to the lack of time synchronicity in source data, requiring a mechanism to effectively analyze and count these data while ensuring data integrity and validity.
Innovation Solution
A threshold tracking system that sets a working time frame to accept inputs, maintains a timeline divided into periods, and tracks threshold breaches by calculating input values over specified thresholds, allowing for real-time analysis of unordered inputs and detection of event rate changes despite variances in event origin time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If real-time analysis is performed on multiple events from disparate sources, then event detection capability is improved, but data reliability deteriorates due to lack of time synchronicity
Solution Approach 1:
The system segments the continuous event stream into discrete time periods and divides events into different categories (threshold events, distinct field events, etc.). This segmentation allows independent processing of events from disparate sources while maintaining overall system reliability through structured temporal organization.
Solution Approach 2:
The patent introduces an intermediary temporal framework that mediates between events from disparate sources with different time synchronicity. This framework acts as a buffer and coordination layer, allowing events to be processed in a standardized temporal context without requiring direct time synchronization between source systems.
2Stability of the object's composition
If a temporal framework is constructed to handle unordered inputs, then data organization is improved, but system complexity increases
Solution Approach 1:
The system implements periodic action by dividing time into discrete periods and processing events in a periodic manner. Events are organized into time periods, and the system periodically evaluates threshold breaches and distinct field occurrences within each period. This periodic structure provides stable data organization without requiring complex continuous processing mechanisms.
3Measurement precision
If threshold tracking is performed over specified time periods, then measurement precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary action by pre-defining time periods and threshold criteria before event processing begins. Time periods are established in advance, and threshold values are pre-configured. This allows events to be quickly evaluated against predetermined criteria without requiring complex real-time calculations, thus maintaining high measurement precision while reducing processing time.
Data Source
AI summary
A threshold tracking system enabling users to arrange input data according to a set time of input creation is disclosed. The tracking system defines threshold variables that maintain counts of inputs over a set threshold time and the input values associated with each count. The threshold variables also maintain timelines, which are divided into time periods. Information may be stored in a working memory, which utilizes a scheduler to update state variable values.